AI Architect

We are looking for an experienced AI Architect with 3+ years of experience in AI/GenAI architecture, agentic AI, LLM applications, and production AI systems. The candidate will be responsible for translating business requirements into scalable AI solutions, designing end-to-end AI/agent architectures, and providing technical leadership throughout the development and deployment lifecycle.

Roles & Responsibilities

• Design end-to-end AI/GenAI architecture, including system components, data flows, agent flows, API integrations, and deployment architecture.
• Translate business and functional requirements into scalable, secure, and production-ready AI solutions.
• Design and implement Agentic AI systems, including AI agents, planning, reasoning, task decomposition, routing, and orchestration.
• Design multi-agent architectures, including SupervisorWorker patterns, agent delegation, handoffs, coordination, and failure/recovery mechanisms.
• Evaluate and select appropriate LLMs/models based on use cases, performance, cost, latency, and reliability.
• Design and implement RAG architectures, vector search, embeddings, retrieval strategies, and knowledge-based AI solutions.
• Architect tool calling, function calling, API integrations, and enterprise service integrations for AI agents.
• Design and integrate MCP (Model Context Protocol)-based tool ecosystems and connect AI agents with enterprise applications and services.
• Define AI workflow and state-management architectures, including agent memory, context management, and conversation state.
• Establish AI evaluation, guardrails, observability, monitoring, security, and reliability practices for production systems.
• Prepare and maintain HLD/LLD, architecture diagrams, technical specifications, and solution documentation.
• Define AI project technical roadmaps, milestones, delivery plans, and development priorities.
• Work closely with developers, project managers, business teams, and other technical stakeholders to ensure successful project delivery.
• Provide technical leadership and guidance to AI/ML development teams and support architectural decision-making.
• Review existing AI solutions and identify opportunities for performance, scalability, cost, and reliability improvements.
• Lead the deployment of AI solutions using Cloud platforms, Docker, APIs, and production infrastructure.
• Ensure development follows appropriate coding standards, security practices, architecture principles, and deployment guidelines.
• Stay updated with emerging technologies in GenAI, LLMs, Agentic AI, MCP, RAG, and AI orchestration frameworks.

Good to Have

• Experience in real-time Voice AI / Conversational AI
• Experience with voice agents and real-time AI workflows
• Experience integrating AI systems with enterprise applications
• Experience leading or mentoring AI development teams